/*
 * Licensed to the Apache Software Foundation (ASF) under one or more
 * contributor license agreements.  See the NOTICE file distributed with
 * this work for additional information regarding copyright ownership.
 * The ASF licenses this file to You under the Apache License, Version 2.0
 * (the "License"); you may not use this file except in compliance with
 * the License.  You may obtain a copy of the License at
 *
 *    http://www.apache.org/licenses/LICENSE-2.0
 *
 * Unless required by applicable law or agreed to in writing, software
 * distributed under the License is distributed on an "AS IS" BASIS,
 * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 * See the License for the specific language governing permissions and
 * limitations under the License.
 */

package demo.spark.examples.streaming;

import com.google.common.collect.Lists;
import demo.vo.JavaRecord;
import org.apache.spark.SparkConf;
import org.apache.spark.SparkContext;
import org.apache.spark.api.java.JavaRDD;
import org.apache.spark.api.java.StorageLevels;
import org.apache.spark.api.java.function.FlatMapFunction;
import org.apache.spark.api.java.function.Function;
import org.apache.spark.api.java.function.VoidFunction2;
import org.apache.spark.sql.Dataset;
import org.apache.spark.sql.Row;
import org.apache.spark.sql.SQLContext;
import org.apache.spark.streaming.Durations;
import org.apache.spark.streaming.Time;
import org.apache.spark.streaming.api.java.JavaDStream;
import org.apache.spark.streaming.api.java.JavaReceiverInputDStream;
import org.apache.spark.streaming.api.java.JavaStreamingContext;

import java.util.Iterator;
import java.util.regex.Pattern;

/**
 * Use DataFrames and SQL to count words in UTF8 encoded, '\n' delimited text received from the
 * network every second.
 * <p>
 * Usage: JavaSqlNetworkWordCount <hostname> <port>
 * <hostname> and <port> describe the TCP server that Spark Streaming would connect to receive data.
 * <p>
 * To run this on your local machine, you need to first run a Netcat server
 * `$ nc -lk 9999`
 * and then run the example
 * `$ bin/run-example demo.spark.examples.streaming.JavaSqlNetworkWordCount localhost 9999`
 */

public final class JavaSqlNetworkWordCount {
    private static final Pattern SPACE = Pattern.compile(" ");

    public static void main(String[] args) throws InterruptedException {
        if (args.length < 2) {
            System.err.println("Usage: JavaNetworkWordCount <hostname> <port>");
            System.exit(1);
        }

        // Create the context with a 1 second batch size
        SparkConf sparkConf = new SparkConf()
                .setAppName("JavaSqlNetworkWordCount");
        JavaStreamingContext ssc = new JavaStreamingContext(sparkConf, Durations.seconds(1));

        // Create a JavaReceiverInputDStream on target ip:port and count the
        // words in input stream of \n delimited text (eg. generated by 'nc')
        // Note that no duplication in storage level only for running locally.
        // Replication necessary in distributed scenario for fault tolerance.
        JavaReceiverInputDStream<String> lines = ssc.socketTextStream(
                args[0], Integer.parseInt(args[1]), StorageLevels.MEMORY_AND_DISK_SER);
        JavaDStream<String> words = lines.flatMap(new FlatMapFunction<String, String>() {
            @Override
            public Iterator<String> call(String x) {
                return Lists.newArrayList(SPACE.split(x)).iterator();
            }
        });

        // Convert RDDs of the words DStream to DataFrame and run SQL query
        words.foreachRDD(new VoidFunction2<JavaRDD<String>, Time>() {
                    @Override
                    public void call(JavaRDD<String> rdd, Time time) throws Exception {
                        SQLContext sqlContext = JavaSQLContextSingleton.getInstance(rdd.context());

                        // Convert JavaRDD[String] to JavaRDD[bean class] to DataFrame
                        JavaRDD<JavaRecord> rowRDD = rdd.map(new Function<String, JavaRecord>() {
                            public JavaRecord call(String word) {
                                JavaRecord record = new JavaRecord();
                                record.setWord(word);
                                return record;
                            }
                        });
                        Dataset<Row> wordsDataFrame = sqlContext.createDataFrame(rowRDD, JavaRecord.class);

                        // Register as table
                        wordsDataFrame.registerTempTable("words");

                        // Do word count on table using SQL and print it
                        Dataset<Row> wordCountsDataFrame =
                                sqlContext.sql("select word, count(*) as total from words group by word");
                        System.out.println("========= " + time + "=========");
                        wordCountsDataFrame.show();
                    }
                });

        ssc.start();
        ssc.awaitTermination();
    }
}

/**
 * Lazily instantiated singleton instance of SQLContext
 */
class JavaSQLContextSingleton {
    static private transient SQLContext instance = null;

    static public SQLContext getInstance(SparkContext sparkContext) {
        if (instance == null) {
            instance = new SQLContext(sparkContext);
        }
        return instance;
    }
}
